In hybrid electric vehicles, it can be beneficial to have an accurate battery capacity estimate. For example, battery capacity can be used as an input to other algorithms such as those used to determine battery state-of-charge (SOC), to balance cells within the battery pack, or to determine the range of a hybrid electric vehicle, to cite a few possibilities.
One conventional way to estimate battery capacity is to take the known capacity of the battery when it was new, keep track of various usage-related parameters such as the total amount of charge flowing into and/or out of the battery since it was new, and then estimate battery capacity degradation over time based on this history. Historical usage techniques such as this, however, can be less than desirable in terms of accuracy, robustness, cost effectiveness, etc.
For instance, such techniques can result in fairly rudimentary estimates that lack the required level of accuracy for certain purposes, like vehicle range estimates. Furthermore, these types of techniques are not always robust because a loss of the historical usage data can result in the system being unable to accurately calculate battery capacity. Consider a vehicle service event where a battery control module containing the historical usage data has malfunctioned and needs to be replaced. Under normal circumstances, the new replacement module would not have the historical usage data from the previous broken module and, therefore, would be unable to generate accurate battery capacity estimates. A similar situation can occur when just the battery pack or a portion of the battery pack is replaced, but not the battery control module; this too, results in a scenario where the historical usage data does not correspond to the actual battery pack being monitored. In view of this, battery packs and control modules are oftentimes replaced in sets so as to avoid the issues described above, thereby resulting in additional costs.